Lead Data Architect

About the role

As a Lead Data Architect, you will play a pivotal role in driving our database strategy across all products. This role demands profound expertise in data architecture to analyze, design, and implement complex systems ensuring robust, scalable solutions that support our business goals. Your expertise will ensure that our data infrastructure is robust, scalable, and aligned with our mission, enabling us to harness the power of data to improve healthcare delivery and support our ongoing commitment to clinical research and our patients.

Responsibilities

• Design, build, and manage the organization's data infrastructure, ensuring it is accessible, reliable, and secure.
• Create the blueprint for how data is collected, stored, processed, and used to support decision-making and business operations.
• Develop and implement a comprehensive data strategy aligned with business goals, including understanding data needs and creating a roadmap for effective data management.
• Design conceptual, logical, and physical data models that represent the structure and relationships of data within the organization.
• Create and maintain the overall data architecture framework, including databases, data warehouses, data lakes, and other data systems.
• Develop and implement data mapping rules to transform data from source systems to target systems, ensuring data accuracy and consistency.
• Design and implement processes for integrating data from various sources, ensuring data consistency and accuracy.
• Establish data governance policies and procedures to ensure data quality, security, and HIPAA compliance across all data systems and platforms.
• Evaluate and recommend data management technologies and tools to support the organization's data needs.
• Identify and resolve data-related issues, ensuring data integrity and reliability.
• Design and implement architectures that seamlessly integrate AI models and algorithms with existing data infrastructures, including cloud-native and legacy systems.
• Create and maintain documentation for database architecture, procedures, and standards.
• Work closely with stakeholders, including business analysts, data scientists, and IT professionals, to understand data requirements and translate them into technical solutions.
• Influence projects to make decisions related to data strategies, including data quality, data architecture, and data management best practices.

Requirements

• Minimum of 7 years of experience in enterprise data architecture, including data requirements collection, data architecture analysis, evaluation, documentation, data modeling, design, development, model validation, and data integration in modern data platforms (e.g., Azure, Databricks, Snowflake).
• Bachelor’s Degree in Computer Science, Information Systems, Engineering, or equivalent experience.
• Minimum 10 years of experience in database engineering/management.
• Knowledge of software development methodologies (e.g., Agile, DevOps, SDLC, CI/CD, GitHub).
• 7+ years' experience working with data sources (e.g., APIs) and databases such as Oracle, PostgreSQL, SQL Server, and cloud databases.
• Knowledge of cloud technologies like Azure (Data Factory, Databricks), AWS.
• Strong knowledge of industry best practices, including code coverage.
• Strong knowledge of database concepts, data modeling techniques, system performance analysis and tuning, and data warehousing concepts.
• Knowledge of various operating systems such as Linux, Unix, and Windows.
• Ability to write complex queries and perform advanced database operations using SQL.

Preferred Skills

• Expertise in modern cloud-native database solutions.
• Experience with database migration tools and strategies, including handling zero-downtime migrations and data synchronization.
• Proficiency in infrastructure-as-code and automation tools (Terraform) for database deployment and management.
• Ability to design scalable database architectures that support microservices and distributed systems.
• Experience with various database patterns (CQRS, event sourcing, sharding strategies).
• Understanding of data modeling for both relational and NoSQL databases.

About Sarah Cannon Research Institute

Sarah Cannon Research Institute (SCRI) is one of the world’s leading oncology research organizations conducting community-based clinical trials. Focused on advancing therapies for patients over the last three decades, SCRI is a leader in drug development. In 2022, SCRI formed a joint venture with former US Oncology Research to expand clinical trial access across the country. It has conducted more than 850 first-in-human clinical trials since its inception and contributed to pivotal research that has led to the majority of new cancer therapies approved by the FDA in the past decade. SCRI’s research network brings together more than 1,300 physicians who are enrolling patients into clinical trials at more than 200 locations in 20+ states across the U.S.

Benefits

We care about the well-being of the patients and communities we serve, and that starts with caring for our people. That’s why we have a Total Rewards package that includes comprehensive benefits to support physical, mental, and financial well-being. Our Total Rewards offerings serve the different needs of our diverse colleague population and ensure they are the healthiest versions of themselves. For more information regarding benefits through our parent company, McKesson, please click here.

Pay

As part of Total Rewards, we are proud to offer a competitive compensation package. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered.